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Top TensorFlow Certifications



TensorFlow is a popular open-source machine learning framework used to train neural networks for a range of tasks. It is one of the most in-demand frameworks available, and it is crucial for learning how to apply machine learning skills to build and train models.

Here is a look at the top TensorFlow certifications on the market:

1. DeepLearning.AI TensorFlow Developer Professional Certificate

This is one of the best TensorFlow certifications available, useful for those looking to learn the skills needed to develop powerful models. This hands-on Professional Certificate program consists of four courses that teach you how to build scalable AI-powered applications. Upon completing the program, you will know how to improve network performance using convolutions, train it to identify real-world images, and teach machines how to understand, analyze, and respond to human speech.

Here are some of the key aspects of this certification:

  • Handle real-world image data
  • Prevent overfitting, including augmentation and dropout
  • Use TensorFlow to develop natural language processing systems
  • Apply RNNs, GRUs, and LSTMs as you use text repositories to train them
  • 16 Python programming assignments
  • Duration: 4 months to complete, 5 hours/week

2. TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning 

This program is aimed at software developers with some prior experience in coding who are looking to build on those skills. The courses demonstrate the techniques for implementing foundational principles of machine learning and deep learning with TensorFlow. The program is also useful for learning how to build scalable models that can be used to tackle real-world problems.

Here are some of the key aspects of this certification:

  • Aimed at those with prior experience in Python
  • Instructors well equipped with examples
  • Tips, techniques, and assessments
  • Flexible deadlines
  • Building a basic neural network for computer vision application
  • Duration: 4 weeks, 4 to 5 hours/week

3. TensorFlow in Practice Specialization (Coursera) 

This certification is vital to developers who want to become proficient with the tools needed to build scalable AI-powered algorithms in TensorFlow. The specialized program has four different courses designed to provide an understanding of how TensorFlow works and major concepts. Upon completing this program, you will know how to build and train neural networks, train networks to identify real-world images, and improve its performance with convolutions.

Here are some of the key aspects of this certification:

  • Comprehensive, specialized program
  • Learn the best practices for TensorFlow
  • Processing text, representing sentences as vectors, inputting data to a neural network, and training AI
  • Teach machines how to understand, analyze, and respond to human speech
  • Duration: 1 month

4. TensorFlow Data and Deployment Specialization (Coursera)

This specialization program is aimed at those looking to learn new ways of utilizing data effectively while training a model, and it prepares you for different distribution scenarios. The program has four different courses, and you will learn how to train and run machine learning models in browsers and mobile applications before tackling more advanced concepts.

Here are some of the key aspects of this certification:

  • Video lectures, quizzes, graded assignments, and hands-on projects
  • Leveraging built-in datasets with a few lines of code
  • TensorFlow Serving, Hub, Tensor Board, and other TensorFlow features
  • Gain skills in Machine Learning, TensorFlow, Advanced Deployment, Object Detection, and JavaScript
  • Running models in your browser with TensorFlow.js
  • Duration: 1 month

5. Deep Learning with TensorFlow 2.0 Certification

This program teaches the foundational techniques of machine learning with TensorFlow. It covers concepts such as data manipulation and supervised algorithms, and it provides hands-on experience with every algorithm in TensorFlow. The instructors are directly accessible through live sessions.

Here are some of the key aspects of this certification:

  • Supervised learning
  • Foundations of neural network designs
  • Implementing unsupervised learnings methods
  • Live lectures
  • Duration: 5 weeks, 30 hours total

6. Machine Learning with TensorFlow on Google Cloud Platform

This machine learning specialization program was developed by Google Cloud, and it uses lectures about building ML models. There are introductory lessons covering machine learning uses and why it is important, as well as lessons on TensorFlow. It is aimed at creating, training, and deploying ML models.

Here are some of the key aspects of this certification:

  • Useful for beginner machine learning data scientists
  • Structured and specialized curriculum with 5 courses
  • Hands-on experience
  • Duration: 1 month, 14 hours/week 

7. Deep Learning with TensorFlow

This course is aimed at those with a basic grasp of machine learning, Python, and deep learning. It helps you utilize and enhance those skills by covering basic concepts, main functions, operations, and execution pipeline. This program will help you time the weights and biases while neural networks are being trained, and it will cover different types of deep architectures.

Here are some of the key aspects of this certification:

  • Framework for curve fitting, regression, classification, and minimization of the error function
  • Deep architectures such as recurrent networks, autoencoder, and convolutional networks
  • Structured course
  • Free study materials and videos
  • Interactive tutorials
  • Duration: 5 weeks, 2 to 4 hours/week

If you are looking to develop your TensorFlow skills to become more valuable in today’s machine learning environment, these certifications are vital. With each one offering its own unique features and experience levels, beginners and experts alike can take part.

Alex McFarland is a historian and journalist covering the newest developments in artificial intelligence.